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collaborative research

Redox signaling - reactive oxygen species
(J. Fetrow, L. Poole, Lowther, R. Loeser, McPhail, Torti, Daniel, C. Furdui, King, John, W. Turkett, F. Salsbury)

Redox SignalingOxidation of macromolecules is an important event in many signaling pathways, as well as during oxidative stress-mediated cell damage. Generation of reactive oxygen species is under investigation by an interdisciplinary group of NIH-supported biochemists and chemists (Poole, Lowther, Loeser, McPhail, Torti, Daniel, Furdui, King) and computational scientists and mathematicians (John, Turkett, Salsbury) some of whom have worked together for >5 years with support from the NSF-NIGMS program in Computational Biology. Investigations focus on signaling-generated posttranslational modifications and on antioxidant enzymes that control H2O2 levels in cells and protect against oxidative stress and cancer. The sites, mechanisms, and consequences of protein thiol oxidation are defined through synthesis of unique protein labels followed by mass spectrometry studies to evaluate processing of these proteins. Bioinformatics approaches are applied to data on reactive cysteine sites to ask how redox modifications affect signal transduction, and to predict protein sites susceptible to oxidative modification.

Nitric oxide signaling
(D. Kim-Shapiro, S. B. King, G.Miller, L. Poole)

The biological function of nitric oxide (NO) is investigated using a combination of organic chemistry, biochemistry, and biophysics (Kim-Shapiro, King, Miller, Poole). NO participates in the control of blood flow, blood pressure, neurotransmission, and immune response. This NIH-supported team, which has worked together for > 10 years, combines synthesis and evaluation of new organic compounds with studies on the reactions of NO with biological molecules. Researchers examine the development of organic molecules as sources of nitrite and the effect of dietary nitrates on NO levels. The effects of NO and hydroxyurea on sickle cell hemoglobin are studied using spectroscopic techniques that alter the biophysical properties of this molecule.

Flavinoid Signaling

Hormonal control of phenylpropanoid synthesis
(G. Muday, W. Turkett, E. Allen, J. Fetrow, B. Winkel, R. Helm)

A team of WFU (including Muday, Turkett, Allen, Fetrow) and Virginia Tech Investigators (Winkel and Helm) explores hormonal control of secondary metabolism in plants. This project is NSF-supported through the Arabidopsis 2010 Program. Phenylpropanoid biosynthesis is a key plant secondary metabolic pathway that generates end products regulating auxin transport; phenylpropanoids also possess anti-oxidant and anti-cancer properties. Researchers examine gene and protein expression and data on metabolites produced in response to elevated levels of hormones auxin and ethylene. This nascent group grew through participation of its members in the SCB program.

Adipokine controls of metabolism and food consumption
(G. Miller, W. Pratt, G. Muday, B. Xue, C. Browne)

This team (Miller, Pratt, Muday, Xue, Browne) has interests in adipose-cell derived hormones leptin and adiponectin, including signals that control their synthesis, signaling pathways that transduce their activity in target cells, their effects on food consumption in mammals, and mechanisms by which exercise and diet control their synthesis and activity. These researchers worked individually for a number of years and through the development of the molecular signaling group have begun to develop collaborative research.

Bioinformatics and functional analysis of receptors and channels
(S. Farbach, E. Johnson, W. Silver)

Steroid and peptide hormones are key regulators of nervous system structure and function, and provide striking examples of conserved function across phyla. Also striking is the conservation of structure and molecular mechanisms of receptors for these signals: in all animals, members of the nuclear receptor superfamily mediate the effects of steroid hormones, while G-protein coupled receptors (GPCRs) mediate the effects of peptides. With NSF support, researchers utilize bioinformatics as the basis for physiological studies informed by identified receptors and aided by modern methods for analysis of gene expression and creation of targeted mutations. Fahrbach (nuclear receptors), E Johnson (GPCRs), and Silver (TRP channels) use insects and rodents to investigate the central nervous system. Through participation in the molecular signaling group, these investigators have begun joint projects.

outline of DASP procedureFunctional site analysis and drug discovery
(J. Fetrow, L. Poole, F. Salsbury, W. Turkett)

Sequence and structural genomics projects have identified and predicted molecular functions in proteins, yet researchers still cannot determine biological mechanisms of, for example, catalysis or substrate specificity or inhibitor binding, without detailed biochemical and biophysical analysis of a single protein. While structural genomics projects are providing the necessary data, they are not being used to reveal the general principles underlying biological mechanism. We are using sequence, structure, bioinformatics, and biophysical methods to characterize the molecular function sites of protein superfamilies. Our tools include fuzzy functional forms (FFFs), active site profilling (DASP), PASSS, and MEAD for electrostatic analysis. The research program focuses on the following objectives: 1) characterizing the sequence and structure of functional-site features and using the results to develop methods for clustering the peroxiredoxin family; 2) analyzing the electrostatics, including ionizable residue pKas, residues affecting these pKas, and electrostatic potential, at peroxiredoxin functional sites and testing them experimentally; 3) integrating the electrostatic, sequence and structural information to create a robust profiling method that can identify peroxiredoxin subfamilies, then making it available; and 4) using it to create active-site signatures and profiles for a well-studied and important set of protein superfamilies and making these data available. Crossing the gap from molecular function to biological mechanism requires integrating sequence, structure, and physical-chemical data. The detailed functional site analysis of protein superfamilies is yielding insights into biological mechanisms, leading to hypotheses that can be experimentally tested. In the long term, the resulting methods will enable more accurate functional site identification from sequence. The development of general concepts for identifying and classifying molecular functional-site features will advance the design of enzymes with improved, altered, or novel activity, and of inhibitors (or lead compounds), an early step in the pharmaceutical drug-discovery process.ribbon figure of protein with active sites


Development of computational algebra and Bayesian tools for biological modeling
(E. Allen, L. Daniel, J. Fetrow, D. John, J. Norris, L. Poole, W. Turkett)

Development of ComputationalPredicting biological networks that underlie experimental data is a major, unsolved problem in modern biology. Constructing models from time course experimental data is particularly difficult, as the number of time points is usually fewer than the number of measured genes or proteins. We are developing computational algebra and Bayesian approaches to modeling such data. Although the number of modified proteins and measured biological endpoints that respond (i.e., the number of variables) exceeds the number of time points that can be collected (i.e., the number of equations), by considering the network under various conditions and by applying game theoretic methods to multiple discretizations of the data, consensus models can be constructed. These models represent aspects of the underlying biological network, identifying dependencies between protein modifications and biological responses. This collaboration among researchers in the departments of Biochemistry, Computer Science, Mathematics, and Physics at Wake Forest University aims to develop theory, algorithms, computational tools, and research methodologies for the network modeling of time course data.

Modeling signaling networks and transcriptional regulatory networks in osteoarthritis
(E. Allen, J. Fetrow, C. Ferguson, D. John, I. Leng, R. Loeser, J. Norris, W. Turkett, C. Carlson [Univ Minnesota])

Modeling SignalingThe long-term goal of this project is to provide a better understanding of the basic cellular and molecular mechanisms driving joint tissue destruction during the development of osteoarthritis (OA). We are utilizing a systems and computational biology approach to map the transcriptional regulatory networks that underlie development of OA in a stage-specific, whole organ, manner. By integrating this transcriptional regulatory network with publicly available information on signaling pathways and protein-protein interaction networks, we are: 1) identifying key genes and proteins that could serve as novel targets for disease modifying therapy, as well as novel stage-specific biomarkers; and 2) identifying pathways that are involved in the disease process, which will enhance our understanding of mechanism. Our approach utilizes a recently developed mouse model of osteoarthritis (destabilization of the medial meniscus). Advantages of this model include: it is biomechanical; damage to the meniscus is a common feature of human OA; it mimics the joint pathology of human OA; and it allows for collection of time course data (early, middle, and late disease stages). Furthermore, the wide availability of transgenic animals permits the future manipulation of identified pathways to test the role of candidate genes and proteins in the network that underlies the development of OA. This project brings together a team of scientists with expertise in computational biology, basic molecular and translational research in OA, surgical models of OA, and the histological evaluation of OA. We aim to provide a comprehensive picture of the OA disease process, thus providing unprecedented insight into the mechanism of that process with the future promise of discovering novel pathways and drug targets responsible for the initiation and progression of the disease.

Allosteric signaling of protein-nucleic acid interactions - translational machinery
(Alexander, Salsbury, J. Curran)

These NSF- and NIH-supported researchers (Alexander, Salsbury, Curran) utilize bench and computational methods to dissect intramolecular protein functional networks in aminoacyl-tRNA synthetases and study interactions between the ribosomal coding sites.  Here molecular signaling consists of conformational changes within proteins induced by nucleic acid binding. Combining functional and structural studies of translation components will lead to better understanding of this critical biological operation

Allosteric signaling of protein-nucleic acid interactions - DNA damage pathways
(K. Scarpinato, F. Salsbury, M. Guthold, A. McCauley)

Mismatch repair proteins change conformation upon binding DNA lesions and initiate two distinct intracellular signaling cascades, one leading to DNA damage repair, the other to cell death. In both pathways, survival of the organism is dependent on allosteric signaling events. This NIH- and NSF-supported research team (Scarpinato, Salsbury, Guthold, McCauley) applies computational methods to model protein conformational changes resulting from nucleic acid binding; models are tested using cell biological, biochemical, and biophysical methods such as atomic force microscopy, confocal microscopy, and kinetic analysis of protein variants. This approach provides students with training in a variety of synergistic methods at the interface of physical, biological, and computational sciences

Mechanical signaling through biological polymers
(M. Guthold, D. Hantgan, J. Macosko, M. Tytell)

This team, supported by NSF- and the American Heart Association, (Guthold, Hantgan, Macosko, Tytell) examines mechanical signaling transmission in and between cells, with a focus on biological polymers such as fibrin and microtubule/integrin networks. Using atomic force microscopy and fluorescence microscopy, this team investigates the strength of single biological bonds, the mechanical properties of biological fibers, and the signaling regulated mechanism that controls cargo shuttling inside nerve cells.